PNAD Contínua
Dados: 2012 - 2024 (Brasil)
Dados: 2012 - 2024 (Brasil)
Fernanda Kelly R. Silva | www.fernandakellyrs.com
19/11/2025
---
title: "PNAD Contínua" # Título do relatório
subtitle: "**Dados: 2012 - 2024 (Brasil)**"
author: "Fernanda Kelly R. Silva | www.fernandakellyrs.com"
lang: pt
date: "`r format(Sys.Date())`"
date-format: short
toc: true
format:
html:
embed-resources: true
#css: ["custom.css"]
code-fold: false
code-tools: true
theme:
light: cosmo
dark: superhero
#title-block-banner: "#874a9c"
code-annotations: hover
execute:
warning: false
message: false
echo: false
---
```{r}
options(timeout = 600)
```
```{r}
#| echo: false
#| warning: false
#| message: false
# install.packages("PNADcIBGE")
# install.packages("survey")
library(PNADcIBGE)
library(survey)
library(foreign)
library(srvyr)
library(reactable)
library(purrr)
```
# 2012
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc1VISITA_2012.RData")
```
```{r}
dadosPNADc1VISITA_2012 <- dadosPNADc1VISITA_2012 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc1VISITA_2012PR <- dadosPNADc1VISITA_2012 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2012PR <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2012PR)
dadosPNADc1VISITA_2012SRPR <- srvyr::as_survey(dadosPNADc1VISITA_2012PR)
```
### Total de Pessoas
```{r}
table_1P_2012 <- dadosPNADc1VISITA_2012SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2012 <- dadosPNADc1VISITA_2012SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2012 <- dadosPNADc1VISITA_2012SRPR %>%
dplyr::filter(VD4032 != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4032,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc1VISITA_2012SEC <- dadosPNADc1VISITA_2012 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2012SEC <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2012SEC)
dadosPNADc1VISITA_2012SRSEC <- srvyr::as_survey(dadosPNADc1VISITA_2012SEC)
```
### Total de Pessoas
```{r}
table_1S_2012 <- dadosPNADc1VISITA_2012SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2012 <- dadosPNADc1VISITA_2012SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2012 <- dadosPNADc1VISITA_2012SRSEC %>%
dplyr::filter(VD4033 != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4033,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2012 <- dadosPNADc1VISITA_2012SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2012 <- dadosPNADc1VISITA_2012SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2012 <- dadosPNADc1VISITA_2012SRPR %>%
dplyr::filter(VD4032 != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4032,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2012 <- dadosPNADc1VISITA_2012SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2012 <- dadosPNADc1VISITA_2012SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2012 <- dadosPNADc1VISITA_2012SRSEC %>%
dplyr::filter(VD4033 != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4033,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc1VISITA_2012 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc1VISITA_2012 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2012 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc1VISITA_2012 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc1VISITA_2012 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2012 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc1VISITA_2012 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(VD4032, VD4033, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc1VISITA_2012 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2012 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2013
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc1VISITA_2013.RData")
```
```{r}
dadosPNADc1VISITA_2013 <- dadosPNADc1VISITA_2013 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc1VISITA_2013PR <- dadosPNADc1VISITA_2013 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2013PR <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2013PR)
dadosPNADc1VISITA_2013SRPR <- srvyr::as_survey(dadosPNADc1VISITA_2013PR)
```
### Total de Pessoas
```{r}
table_1P_2013 <- dadosPNADc1VISITA_2013SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2013 <- dadosPNADc1VISITA_2013SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2013 <- dadosPNADc1VISITA_2013SRPR %>%
dplyr::filter(VD4032 != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4032,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc1VISITA_2013SEC <- dadosPNADc1VISITA_2013 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2013SEC <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2013SEC)
dadosPNADc1VISITA_2013SRSEC <- srvyr::as_survey(dadosPNADc1VISITA_2013SEC)
```
### Total de Pessoas
```{r}
table_1S_2013 <- dadosPNADc1VISITA_2013SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2013 <- dadosPNADc1VISITA_2013SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2013 <- dadosPNADc1VISITA_2013SRSEC %>%
dplyr::filter(VD4033 != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4033,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2013 <- dadosPNADc1VISITA_2013SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2013 <- dadosPNADc1VISITA_2013SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2013 <- dadosPNADc1VISITA_2013SRPR %>%
dplyr::filter(VD4032 != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4032,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2013 <- dadosPNADc1VISITA_2013SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2013 <- dadosPNADc1VISITA_2013SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2013 <- dadosPNADc1VISITA_2013SRSEC %>%
dplyr::filter(VD4033 != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4033,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc1VISITA_2013 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc1VISITA_2013 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2013 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc1VISITA_2013 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc1VISITA_2013 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2013 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc1VISITA_2013 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(VD4032, VD4033, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc1VISITA_2013 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2013 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2014
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc1VISITA_2014.RData")
```
```{r}
dadosPNADc1VISITA_2014 <- dadosPNADc1VISITA_2014 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc1VISITA_2014PR <- dadosPNADc1VISITA_2014 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2014PR <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2014PR)
dadosPNADc1VISITA_2014SRPR <- srvyr::as_survey(dadosPNADc1VISITA_2014PR)
```
### Total de Pessoas
```{r}
table_1P_2014 <- dadosPNADc1VISITA_2014SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2014 <- dadosPNADc1VISITA_2014SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2014 <- dadosPNADc1VISITA_2014SRPR %>%
dplyr::filter(VD4032 != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4032,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc1VISITA_2014SEC <- dadosPNADc1VISITA_2014 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2014SEC <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2014SEC)
dadosPNADc1VISITA_2014SRSEC <- srvyr::as_survey(dadosPNADc1VISITA_2014SEC)
```
### Total de Pessoas
```{r}
table_1S_2014 <- dadosPNADc1VISITA_2014SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2014 <- dadosPNADc1VISITA_2014SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2014 <- dadosPNADc1VISITA_2014SRSEC %>%
dplyr::filter(VD4033 != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4033,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2014 <- dadosPNADc1VISITA_2014SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2014 <- dadosPNADc1VISITA_2014SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2014 <- dadosPNADc1VISITA_2014SRPR %>%
dplyr::filter(VD4032 != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4032,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2014 <- dadosPNADc1VISITA_2014SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2014 <- dadosPNADc1VISITA_2014SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2014 <- dadosPNADc1VISITA_2014SRSEC %>%
dplyr::filter(VD4033 != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4033,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc1VISITA_2014 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc1VISITA_2014 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2014 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc1VISITA_2014 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc1VISITA_2014 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2014 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc1VISITA_2014 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(VD4032, VD4033, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc1VISITA_2014 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2014 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2015
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc1VISITA_2015.RData")
```
```{r}
dadosPNADc1VISITA_2015 <- dadosPNADc1VISITA_2015 %>%
#ANO 2015 USAR:
dplyr::mutate(V4039C = base::ifelse(is.na(V4039C),
VD4032,
V4039C),
V4056C = base::ifelse(is.na(V4056C),
VD4033,
V4056C)) %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc1VISITA_2015PR <- dadosPNADc1VISITA_2015 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2015PR <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2015PR)
dadosPNADc1VISITA_2015SRPR <- srvyr::as_survey(dadosPNADc1VISITA_2015PR)
```
### Total de Pessoas
```{r}
table_1P_2015 <- dadosPNADc1VISITA_2015SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2015 <- dadosPNADc1VISITA_2015SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2015 <- dadosPNADc1VISITA_2015SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc1VISITA_2015SEC <- dadosPNADc1VISITA_2015 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2015SEC <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2015SEC)
dadosPNADc1VISITA_2015SRSEC <- srvyr::as_survey(dadosPNADc1VISITA_2015SEC)
```
### Total de Pessoas
```{r}
table_1S_2015 <- dadosPNADc1VISITA_2015SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2015 <- dadosPNADc1VISITA_2015SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2015 <- dadosPNADc1VISITA_2015SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2015 <- dadosPNADc1VISITA_2015SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2015 <- dadosPNADc1VISITA_2015SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2015 <- dadosPNADc1VISITA_2015SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2015 <- dadosPNADc1VISITA_2015SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2015 <- dadosPNADc1VISITA_2015SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2015 <- dadosPNADc1VISITA_2015SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc1VISITA_2015 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc1VISITA_2015 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2015 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc1VISITA_2015 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc1VISITA_2015 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2015 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc1VISITA_2015 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc1VISITA_2015 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2015 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2016
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc1VISITA_2016.RData")
```
```{r}
dadosPNADc1VISITA_2016 <- dadosPNADc1VISITA_2016 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc1VISITA_2016PR <- dadosPNADc1VISITA_2016 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2016PR <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2016PR)
dadosPNADc1VISITA_2016SRPR <- srvyr::as_survey(dadosPNADc1VISITA_2016PR)
```
### Total de Pessoas
```{r}
table_1P_2016 <- dadosPNADc1VISITA_2016SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2016 <- dadosPNADc1VISITA_2016SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2016 <- dadosPNADc1VISITA_2016SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc1VISITA_2016SEC <- dadosPNADc1VISITA_2016 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2016SEC <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2016SEC)
dadosPNADc1VISITA_2016SRSEC <- srvyr::as_survey(dadosPNADc1VISITA_2016SEC)
```
### Total de Pessoas
```{r}
table_1S_2016 <- dadosPNADc1VISITA_2016SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2016 <- dadosPNADc1VISITA_2016SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2016 <- dadosPNADc1VISITA_2016SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2016 <- dadosPNADc1VISITA_2016SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2016 <- dadosPNADc1VISITA_2016SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2016 <- dadosPNADc1VISITA_2016SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2016 <- dadosPNADc1VISITA_2016SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2016 <- dadosPNADc1VISITA_2016SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2016 <- dadosPNADc1VISITA_2016SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc1VISITA_2016 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc1VISITA_2016 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2016 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc1VISITA_2016 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc1VISITA_2016 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2016 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc1VISITA_2016 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc1VISITA_2016 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2016 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2017
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc1VISITA_2017.RData")
```
```{r}
dadosPNADc1VISITA_2017 <- dadosPNADc1VISITA_2017 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc1VISITA_2017PR <- dadosPNADc1VISITA_2017 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2017PR <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2017PR)
dadosPNADc1VISITA_2017SRPR <- srvyr::as_survey(dadosPNADc1VISITA_2017PR)
```
### Total de Pessoas
```{r}
table_1P_2017 <- dadosPNADc1VISITA_2017SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2017 <- dadosPNADc1VISITA_2017SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2017 <- dadosPNADc1VISITA_2017SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc1VISITA_2017SEC <- dadosPNADc1VISITA_2017 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2017SEC <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2017SEC)
dadosPNADc1VISITA_2017SRSEC <- srvyr::as_survey(dadosPNADc1VISITA_2017SEC)
```
### Total de Pessoas
```{r}
table_1S_2017 <- dadosPNADc1VISITA_2017SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2017 <- dadosPNADc1VISITA_2017SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2017 <- dadosPNADc1VISITA_2017SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2017 <- dadosPNADc1VISITA_2017SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2017 <- dadosPNADc1VISITA_2017SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2017 <- dadosPNADc1VISITA_2017SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2017 <- dadosPNADc1VISITA_2017SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2017 <- dadosPNADc1VISITA_2017SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2017 <- dadosPNADc1VISITA_2017SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc1VISITA_2017 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc1VISITA_2017 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2017 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc1VISITA_2017 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc1VISITA_2017 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2017 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc1VISITA_2017 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc1VISITA_2017 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2017 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2018
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc1VISITA_2018.RData")
```
```{r}
dadosPNADc1VISITA_2018 <- dadosPNADc1VISITA_2018 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc1VISITA_2018PR <- dadosPNADc1VISITA_2018 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2018PR <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2018PR)
dadosPNADc1VISITA_2018SRPR <- srvyr::as_survey(dadosPNADc1VISITA_2018PR)
```
### Total de Pessoas
```{r}
table_1P_2018 <- dadosPNADc1VISITA_2018SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2018 <- dadosPNADc1VISITA_2018SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2018 <- dadosPNADc1VISITA_2018SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc1VISITA_2018SEC <- dadosPNADc1VISITA_2018 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2018SEC <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2018SEC)
dadosPNADc1VISITA_2018SRSEC <- srvyr::as_survey(dadosPNADc1VISITA_2018SEC)
```
### Total de Pessoas
```{r}
table_1S_2018 <- dadosPNADc1VISITA_2018SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2018 <- dadosPNADc1VISITA_2018SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2018 <- dadosPNADc1VISITA_2018SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2018 <- dadosPNADc1VISITA_2018SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2018 <- dadosPNADc1VISITA_2018SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2018 <- dadosPNADc1VISITA_2018SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2018 <- dadosPNADc1VISITA_2018SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2018 <- dadosPNADc1VISITA_2018SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2018 <- dadosPNADc1VISITA_2018SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc1VISITA_2018 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc1VISITA_2018 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2018 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc1VISITA_2018 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc1VISITA_2018 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2018 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc1VISITA_2018 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc1VISITA_2018 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2018 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2019
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc1VISITA_2019.RData")
```
```{r}
dadosPNADc1VISITA_2019 <- dadosPNADc1VISITA_2019 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc1VISITA_2019PR <- dadosPNADc1VISITA_2019 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2019PR <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2019PR)
dadosPNADc1VISITA_2019SRPR <- srvyr::as_survey(dadosPNADc1VISITA_2019PR)
```
### Total de Pessoas
```{r}
table_1P_2019 <- dadosPNADc1VISITA_2019SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2019 <- dadosPNADc1VISITA_2019SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2019 <- dadosPNADc1VISITA_2019SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc1VISITA_2019SEC <- dadosPNADc1VISITA_2019 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2019SEC <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2019SEC)
dadosPNADc1VISITA_2019SRSEC <- srvyr::as_survey(dadosPNADc1VISITA_2019SEC)
```
### Total de Pessoas
```{r}
table_1S_2019 <- dadosPNADc1VISITA_2019SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2019 <- dadosPNADc1VISITA_2019SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2019 <- dadosPNADc1VISITA_2019SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2019 <- dadosPNADc1VISITA_2019SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2019 <- dadosPNADc1VISITA_2019SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2019 <- dadosPNADc1VISITA_2019SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2019 <- dadosPNADc1VISITA_2019SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2019 <- dadosPNADc1VISITA_2019SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2019 <- dadosPNADc1VISITA_2019SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc1VISITA_2019 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc1VISITA_2019 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2019 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc1VISITA_2019 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc1VISITA_2019 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2019 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc1VISITA_2019 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc1VISITA_2019 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2019 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2020
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc5VISITA_2020.RData")
```
```{r}
dadosPNADc5VISITA_2020 <- dadosPNADc5VISITA_2020 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc5VISITA_2020PR <- dadosPNADc5VISITA_2020 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc5VISITA_2020PR <- PNADcIBGE::pnadc_design(dadosPNADc5VISITA_2020PR)
dadosPNADc5VISITA_2020SRPR <- srvyr::as_survey(dadosPNADc5VISITA_2020PR)
```
### Total de Pessoas
```{r}
table_1P_2020 <- dadosPNADc5VISITA_2020SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2020 <- dadosPNADc5VISITA_2020SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2020 <- dadosPNADc5VISITA_2020SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc5VISITA_2020SEC <- dadosPNADc5VISITA_2020 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc5VISITA_2020SEC <- PNADcIBGE::pnadc_design(dadosPNADc5VISITA_2020SEC)
dadosPNADc5VISITA_2020SRSEC <- srvyr::as_survey(dadosPNADc5VISITA_2020SEC)
```
### Total de Pessoas
```{r}
table_1S_2020 <- dadosPNADc5VISITA_2020SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2020 <- dadosPNADc5VISITA_2020SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2020 <- dadosPNADc5VISITA_2020SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2020 <- dadosPNADc5VISITA_2020SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2020 <- dadosPNADc5VISITA_2020SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2020 <- dadosPNADc5VISITA_2020SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2020 <- dadosPNADc5VISITA_2020SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2020 <- dadosPNADc5VISITA_2020SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2020 <- dadosPNADc5VISITA_2020SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc5VISITA_2020 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc5VISITA_2020 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2020 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc5VISITA_2020 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc5VISITA_2020 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2020 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc5VISITA_2020 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc5VISITA_2020 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2020 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2021
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc5VISITA_2021.RData")
```
```{r}
dadosPNADc5VISITA_2021 <- dadosPNADc5VISITA_2021 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc5VISITA_2021PR <- dadosPNADc5VISITA_2021 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc5VISITA_2021PR <- PNADcIBGE::pnadc_design(dadosPNADc5VISITA_2021PR)
dadosPNADc5VISITA_2021SRPR <- srvyr::as_survey(dadosPNADc5VISITA_2021PR)
```
### Total de Pessoas
```{r}
table_1P_2021 <- dadosPNADc5VISITA_2021SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2021 <- dadosPNADc5VISITA_2021SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2021 <- dadosPNADc5VISITA_2021SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc5VISITA_2021SEC <- dadosPNADc5VISITA_2021 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc5VISITA_2021SEC <- PNADcIBGE::pnadc_design(dadosPNADc5VISITA_2021SEC)
dadosPNADc5VISITA_2021SRSEC <- srvyr::as_survey(dadosPNADc5VISITA_2021SEC)
```
### Total de Pessoas
```{r}
table_1S_2021 <- dadosPNADc5VISITA_2021SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2021 <- dadosPNADc5VISITA_2021SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2021 <- dadosPNADc5VISITA_2021SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2021 <- dadosPNADc5VISITA_2021SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2021 <- dadosPNADc5VISITA_2021SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2021 <- dadosPNADc5VISITA_2021SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2021 <- dadosPNADc5VISITA_2021SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2021 <- dadosPNADc5VISITA_2021SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2021 <- dadosPNADc5VISITA_2021SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc5VISITA_2021 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc5VISITA_2021 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2021 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc5VISITA_2021 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc5VISITA_2021 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2021 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc5VISITA_2021 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc5VISITA_2021 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2021 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2022
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc5VISITA_2022.RData")
```
```{r}
dadosPNADc5VISITA_2022 <- dadosPNADc5VISITA_2022 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc5VISITA_2022PR <- dadosPNADc5VISITA_2022 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc5VISITA_2022PR <- PNADcIBGE::pnadc_design(dadosPNADc5VISITA_2022PR)
dadosPNADc5VISITA_2022SRPR <- srvyr::as_survey(dadosPNADc5VISITA_2022PR)
```
### Total de Pessoas
```{r}
table_1P_2022 <- dadosPNADc5VISITA_2022SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2022 <- dadosPNADc5VISITA_2022SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2022 <- dadosPNADc5VISITA_2022SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc5VISITA_2022SEC <- dadosPNADc5VISITA_2022 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc5VISITA_2022SEC <- PNADcIBGE::pnadc_design(dadosPNADc5VISITA_2022SEC)
dadosPNADc5VISITA_2022SRSEC <- srvyr::as_survey(dadosPNADc5VISITA_2022SEC)
```
### Total de Pessoas
```{r}
table_1S_2022 <- dadosPNADc5VISITA_2022SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2022 <- dadosPNADc5VISITA_2022SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2022 <- dadosPNADc5VISITA_2022SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2022 <- dadosPNADc5VISITA_2022SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2022 <- dadosPNADc5VISITA_2022SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2022 <- dadosPNADc5VISITA_2022SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2022 <- dadosPNADc5VISITA_2022SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2022 <- dadosPNADc5VISITA_2022SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2022 <- dadosPNADc5VISITA_2022SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc5VISITA_2022 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc5VISITA_2022 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2022 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc5VISITA_2022 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc5VISITA_2022 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2022 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc5VISITA_2022 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc5VISITA_2022 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2022 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2023
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc1VISITA_2023.RData")
```
```{r}
dadosPNADc1VISITA_2023 <- dadosPNADc1VISITA_2023 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc1VISITA_2023PR <- dadosPNADc1VISITA_2023 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2023PR <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2023PR)
dadosPNADc1VISITA_2023SRPR <- srvyr::as_survey(dadosPNADc1VISITA_2023PR)
```
### Total de Pessoas
```{r}
table_1P_2023 <- dadosPNADc1VISITA_2023SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2023 <- dadosPNADc1VISITA_2023SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2023 <- dadosPNADc1VISITA_2023SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc1VISITA_2023SEC <- dadosPNADc1VISITA_2023 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2023SEC <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2023SEC)
dadosPNADc1VISITA_2023SRSEC <- srvyr::as_survey(dadosPNADc1VISITA_2023SEC)
```
### Total de Pessoas
```{r}
table_1S_2023 <- dadosPNADc1VISITA_2023SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2023 <- dadosPNADc1VISITA_2023SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2023 <- dadosPNADc1VISITA_2023SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2023 <- dadosPNADc1VISITA_2023SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2023 <- dadosPNADc1VISITA_2023SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2023 <- dadosPNADc1VISITA_2023SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2023 <- dadosPNADc1VISITA_2023SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2023 <- dadosPNADc1VISITA_2023SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2023 <- dadosPNADc1VISITA_2023SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc1VISITA_2023 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc1VISITA_2023 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2023 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc1VISITA_2023 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc1VISITA_2023 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2023 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc1VISITA_2023 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc1VISITA_2023 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2023 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2024
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Visitas/dadosPNADc1VISITA_2024.RData")
```
```{r}
dadosPNADc1VISITA_2024 <- dadosPNADc1VISITA_2024 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc1VISITA_2024PR <- dadosPNADc1VISITA_2024 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2024PR <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2024PR)
dadosPNADc1VISITA_2024SRPR <- srvyr::as_survey(dadosPNADc1VISITA_2024PR)
```
### Total de Pessoas
```{r}
table_1P_2024 <- dadosPNADc1VISITA_2024SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2024 <- dadosPNADc1VISITA_2024SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2024 <- dadosPNADc1VISITA_2024SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc1VISITA_2024SEC <- dadosPNADc1VISITA_2024 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_2024SEC <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_2024SEC)
dadosPNADc1VISITA_2024SRSEC <- srvyr::as_survey(dadosPNADc1VISITA_2024SEC)
```
### Total de Pessoas
```{r}
table_1S_2024 <- dadosPNADc1VISITA_2024SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2024 <- dadosPNADc1VISITA_2024SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2024 <- dadosPNADc1VISITA_2024SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2024 <- dadosPNADc1VISITA_2024SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2024 <- dadosPNADc1VISITA_2024SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2024 <- dadosPNADc1VISITA_2024SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2024 <- dadosPNADc1VISITA_2024SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2024 <- dadosPNADc1VISITA_2024SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2024 <- dadosPNADc1VISITA_2024SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc1VISITA_2024 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc1VISITA_2024 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2024 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc1VISITA_2024 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc1VISITA_2024 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2024 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc1VISITA_2024 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc1VISITA_2024 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2024 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2025
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc1VISITA_25.RData")
```
```{r}
dadosPNADc1VISITA_25 <- dadosPNADc1VISITA_2023 %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc1VISITA_25PR <- dadosPNADc1VISITA_25 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_25PR <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_25PR)
dadosPNADc1VISITA_25SRPR <- srvyr::as_survey(dadosPNADc1VISITA_25PR)
```
### Total de Pessoas
```{r}
table_1P_2025 <- dadosPNADc1VISITA_25SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2025 <- dadosPNADc1VISITA_25SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2025 <- dadosPNADc1VISITA_25SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc1VISITA_25SEC <- dadosPNADc1VISITA_25 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_25SEC <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_25SEC)
dadosPNADc1VISITA_25SRSEC <- srvyr::as_survey(dadosPNADc1VISITA_25SEC)
```
### Total de Pessoas
```{r}
table_1S_2025 <- dadosPNADc1VISITA_25SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2025 <- dadosPNADc1VISITA_25SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2025 <- dadosPNADc1VISITA_25SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2025 <- dadosPNADc1VISITA_25SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2025 <- dadosPNADc1VISITA_25SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2025 <- dadosPNADc1VISITA_25SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2025 <- dadosPNADc1VISITA_25SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2025 <- dadosPNADc1VISITA_25SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2025 <- dadosPNADc1VISITA_25SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc1VISITA_25 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc1VISITA_25 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2025 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc1VISITA_25 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc1VISITA_25 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2025 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc1VISITA_25 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc1VISITA_25 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2025 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# Empilhamento
```{r}
table_1TP <- dplyr::bind_rows(table_1TP_2012,
table_1TP_2013,
table_1TP_2014,
table_1TP_2015,
table_1TP_2016,
table_1TP_2017,
table_1TP_2018,
table_1TP_2019,
table_1TP_2020,
table_1TP_2021,
table_1TP_2022,
table_1TP_2023,
table_1TP_2024,
table_1TP_2025
)
table_2TP <- dplyr::bind_rows(table_2TP_2012,
table_2TP_2013,
table_2TP_2014,
table_2TP_2015,
table_2TP_2016,
table_2TP_2017,
table_2TP_2018,
table_2TP_2019,
table_2TP_2020,
table_2TP_2021,
table_2TP_2022,
table_2TP_2023,
table_2TP_2024,
table_2TP_2025
)
table_3TP <- dplyr::bind_rows(table_3TP_2012,
table_3TP_2013,
table_3TP_2014,
table_3TP_2015,
table_3TP_2016,
table_3TP_2017,
table_3TP_2018,
table_3TP_2019,
table_3TP_2020,
table_3TP_2021,
table_3TP_2022,
table_3TP_2023,
table_3TP_2024,
table_3TP_2025
)
table_1TS <- dplyr::bind_rows(table_1TS_2012,
table_1TS_2013,
table_1TS_2014,
table_1TS_2015,
table_1TS_2016,
table_1TS_2017,
table_1TS_2018,
table_1TS_2019,
table_1TS_2020,
table_1TS_2021,
table_1TS_2022,
table_1TS_2023,
table_1TS_2024,
table_1TS_2025
)
table_2TS <- dplyr::bind_rows(table_2TS_2012,
table_2TS_2013,
table_2TS_2014,
table_2TS_2015,
table_2TS_2016,
table_2TS_2017,
table_2TS_2018,
table_2TS_2019,
table_2TS_2020,
table_2TS_2021,
table_2TS_2022,
table_2TS_2023,
table_2TS_2024,
table_2TS_2025
)
table_3TS <- dplyr::bind_rows(table_3TS_2012,
table_3TS_2013,
table_3TS_2014,
table_3TS_2015,
table_3TS_2016,
table_3TS_2017,
table_3TS_2018,
table_3TS_2019,
table_3TS_2020,
table_3TS_2021,
table_3TS_2022,
table_3TS_2023,
table_3TS_2024,
table_3TS_2025
)
table_1P <- dplyr::bind_rows(table_1P_2012,
table_1P_2013,
table_1P_2014,
table_1P_2015,
table_1P_2016,
table_1P_2017,
table_1P_2018,
table_1P_2019,
table_1P_2020,
table_1P_2021,
table_1P_2022,
table_1P_2023,
table_1P_2024,
table_1P_2025
)
table_2P <- dplyr::bind_rows( table_2P_2012,
table_2P_2013,
table_2P_2014,
table_2P_2015,
table_2P_2016,
table_2P_2017,
table_2P_2018,
table_2P_2019,
table_2P_2020,
table_2P_2021,
table_2P_2022,
table_2P_2023,
table_2P_2024,
table_2P_2025
)
table_3P <- dplyr::bind_rows(table_3P_2012,
table_3P_2013,
table_3P_2014,
table_3P_2015,
table_3P_2016,
table_3P_2017,
table_3P_2018,
table_3P_2019,
table_3P_2020,
table_3P_2021,
table_3P_2022,
table_3P_2023,
table_3P_2024,
table_3P_2025
)
table_1S <- dplyr::bind_rows(table_1S_2012,
table_1S_2013,
table_1S_2014,
table_1S_2015,
table_1S_2016,
table_1S_2017,
table_1S_2018,
table_1S_2019,
table_1S_2020,
table_1S_2021,
table_1S_2022,
table_1S_2023,
table_1S_2024,
table_1S_2025
)
table_2S <- dplyr::bind_rows(table_2S_2012,
table_2S_2013,
table_2S_2014,
table_2S_2015,
table_2S_2016,
table_2S_2017,
table_2S_2018,
table_2S_2019,
table_2S_2020,
table_2S_2021,
table_2S_2022,
table_2S_2023,
table_2S_2024,
table_2S_2025
)
table_3S <- dplyr::bind_rows(table_3S_2012,
table_3S_2013,
table_3S_2014,
table_3S_2015,
table_3S_2016,
table_3S_2017,
table_3S_2018,
table_3S_2019,
table_3S_2020,
table_3S_2021,
table_3S_2022,
table_3S_2023,
table_3S_2024,
table_3S_2025
)
table_1PS <- dplyr::bind_rows(table_1PS_2012,
table_1PS_2013,
table_1PS_2014,
table_1PS_2015,
table_1PS_2016,
table_1PS_2017,
table_1PS_2018,
table_1PS_2019,
table_1PS_2020,
table_1PS_2021,
table_1PS_2022,
table_1PS_2023,
table_1PS_2024,
table_1PS_2025
)
table_2PS <- dplyr::bind_rows(table_2PS_2012,
table_2PS_2013,
table_2PS_2014,
table_2PS_2015,
table_2PS_2016,
table_2PS_2017,
table_2PS_2018,
table_2PS_2019,
table_2PS_2020,
table_2PS_2021,
table_2PS_2022,
table_2PS_2023,
table_2PS_2024,
table_2PS_2025
)
table_3PS <- dplyr::bind_rows(table_3PS_2012,
table_3PS_2013,
table_3PS_2014,
table_3PS_2015,
table_3PS_2016,
table_3PS_2017,
table_3PS_2018,
table_3PS_2019,
table_3PS_2020,
table_3PS_2021,
table_3PS_2022,
table_3PS_2023,
table_3PS_2024,
table_3PS_2025
)
```
# Excel
```{r}
sheets <- list("N TOTAL PRINCIPAL" = table_1TP,
"HABITUAL TOTAL PRINCIPAL" = table_2TP,
"EFETIVA TOTAL PRINCIPAL" = table_3TP,
"N TOTAL SECUNDÁRIO" = table_1TS,
"HABITUAL TOTAL SECUNDÁRIO" = table_2TS,
"EFETIVA TOTAL SECUNDÁRIO" = table_3TS,
"N PRINCIPAL" = table_1P,
"HABITUAL PRINCIPAL" = table_2P,
"EFETIVA PRINCIPAL" = table_3P,
"N SECUNDÁRIO" = table_1S,
"HABITUAL SECUNDÁRIO" = table_2S,
"EFETIVA SECUNDÁRIO" = table_3S,
"N P&S" = table_1PS,
"HABITUAL P&S" = table_2PS,
"EFETIVA P&S" = table_3PS)
writexl::write_xlsx(sheets,
paste0("C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/PNAD_projetos/Dados/tabPSANOS_BR_2.xlsx"))
```